SYCL：未找到内核名称

Question

关于这个问题还有其他类似的问题，但他们的答案并不能解决我的问题：

terminate called after throwing an instance of 'sycl::_V1::runtime_error'   what():  No kernel named _ZTSZ7gpu_CUBEUlvE_ was found -46 (PI_ERROR_INVALID_KERNEL_NAME) 

我有一个 Fortran 代码，它使用包装器来调用 CUDA-C 函数。现在我正在将 CUDA 代码转换为 SYCL 代码（以便在 NVIDIA GPU 中工作）。我也相应地修改了Makefile，所以我使用Clang++来编译SYCL。该错误似乎与链接阶段有关。我正在使用 ifort 编译器进行链接（ifort 管理一些 MPI 依赖项，而 clang++ 不能）。

我单独测试了SYCL代码，效果很好。问题在于将其链接到 Fortran 项目时。您可以通过以下方式重现错误：

runfom.f：

  program runfom
  use MPI
  include 'CUB.f'


  call gpu_init()

  call gpu_CUB()

  end program runfom

CUB.f：

  USE ISO_C_BINDING
  implicit none
  INTERFACE

  SUBROUTINE gpu_init() bind(C, name="gpu_init")
  END SUBROUTINE

  SUBROUTINE gpu_CUB() bind(C, name="gpu_CUB")
  END SUBROUTINE


  END INTERFACE

CUB_kernel.cpp：

#include <sycl/sycl.hpp>
#include <dpct/dpct.hpp>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>

#include <sched.h>
#include <cmath>


extern "C"
{

void gpu_init()
{

  auto platforms = sycl::platform::get_platforms();


  printf("\n \n Checking all devices in the Node: \n");

 for (const auto & platform: platforms){
  auto devices = platform.get_devices();
  for (const auto& device : devices) {


        std::string name = device.get_info<sycl::info::device::name>();
        std::string vendor = device.get_info<sycl::info::device::vendor>();

        // Print device information
        std::cout << "Name: " << name << std::endl;
        std::cout << "Vendor: " << vendor << std::endl;

   }

  }
}

void gpu_CUB(void) {

        const int N=16;

    sycl::device dev_ct1;
    sycl::queue q_ct1(
        dev_ct1, sycl::property_list{sycl::property::queue::in_order()});
    //# Initialize vectors on host
    float A[N] = {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1};
    float B[N] = {2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2};
    float C[N] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};

    //# Allocate memory on device
    float *d_A, *d_B, *d_C;
    d_A = sycl::malloc_device<float>(N, q_ct1);
    d_B = sycl::malloc_device<float>(N, q_ct1);
    d_C = sycl::malloc_device<float>(N, q_ct1);

    //# copy vector data from host to device
    q_ct1.memcpy(d_A, A, N * sizeof(float));
    q_ct1.memcpy(d_B, B, N * sizeof(float));

    q_ct1.single_task<>([=]() {d_C[0]=1.9;} );

    //# copy result of vector data from device to host
    q_ct1.memcpy(C, d_C, N * sizeof(float)).wait();

    //# print result on host
    for (int i = 0; i < N; i++) std::cout<< C[i] << " ";
    std::cout << "\n";

    //# free allocation on device
    sycl::free(d_A, q_ct1);
    sycl::free(d_B, q_ct1);
    sycl::free(d_C, q_ct1);


}

}

生成文件：

FCOMPILE = ftn
SYCLCOMPILE = /mypath/intel/oneapi/compiler/2024.0/bin/compiler/clang++
CCOMPILE = /mypath/intel/oneapi/compiler/2024.0/bin/compiler/clang
DEFS = -DNVIDIA_GPU

FLAGS = $(DEFS) -fast
CFLAGS = $(DEFS)
NVFLAGS = $(DEFS) -fsycl -fsycl-targets=nvptx64-nvidia-cuda -I./ISO_Fortran_binding/include

FFLAGS= $(GENCMPLFLAGS) $(TARGET_ARCH) -cpp
F90FLAGS= $(GENCMPLFLAGS) $(TARGET_ARCH) -cpp

DEPS=CUB.f


LDLIBS = -L/mypath/intel/oneapi/compiler/2024.0/lib -lsycl -lstdc++

COMPILE.c = $(CCOMPILE) $(CFLAGS) -c
COMPILE.f = $(FCOMPILE) $(FFLAGS) -c
COMPILE.cpp = $(SYCLCOMPILE) $(NVFLAGS) -c
COMPILE.f90 = $(FCOMPILE) $(F90FLAGS) -c
LINK.f = $(FCOMPILE) $(FFLAGS)

#  command to compile (not link):
%.o: %.c $(DEPS)
        $(COMPILE.c) -o $@ $<

%.o: %.cpp $(DEPS)
        $(COMPILE.cpp)  -o $@ $<

#  command to compile (not link):
%.o: %.f90 $(DEPS)
        $(COMPILE.f90) -o $@ $<

#  command to compile (not link):
%.o: %.f $(DEPS)
        $(COMPILE.f) -o $@ $<

#  command to link object files:
%: %.o $(DEPS)
        $(LINK.f) $^ $(LDLIBS) -o $@

################################################################
#
# build rule
#
################################################################

runfom: runfom.o CUB_kernel.o
        $(LINK.f) $^ $(LDLIBS) -o $@

clean:  
        rm -f runfom *.o

其中 ftn 是 ifort+MPI 依赖项的包装器。

我用

SYCL_DEVICE_FILTER=cuda SYCL_PI_TRACE=1 ./runfom

执行，得到以下输出：

SYCL_PI_TRACE[basic]: Plugin found and successfully loaded: libpi_cuda.so [ PluginVersion: 14.38.1 ]
SYCL_PI_TRACE[basic]: Plugin found and successfully loaded: libpi_unified_runtime.so [ PluginVersion: 14.37.1 ]

 
 Checking all devices in the Node: 
Name: NVIDIA A100-PCIE-40GB
Vendor: NVIDIA Corporation
SYCL_PI_TRACE[all]: Requested device_type: info::device_type::automatic
SYCL_PI_TRACE[all]: Selected device: -> final score = 500
SYCL_PI_TRACE[all]:   platform: NVIDIA CUDA BACKEND
SYCL_PI_TRACE[all]:   device: NVIDIA A100-PCIE-40GB
terminate called after throwing an instance of 'sycl::_V1::runtime_error'
  what():  No kernel named _ZTSZ7gpu_CUBEUlvE_ was found -46 (PI_ERROR_INVALID_KERNEL_NAME)

我尝试过使用 gfortran，并且在链接语句（在 Makefile 中）中使用了标志顺序，但仍然如此。

有什么想法吗？

Answer 1

您对链接的看法是正确的 - 您也需要在链接阶段使用 icpx （或 clang++）。